Martech stacks are the most stressful part of many marketers’ jobs. In a relatively short period, marketing has gone from low-tech to now spending a significant proportion of effort and budget acquiring and managing technology. Remember when there was a separate ‘digital marketing’ team?
The famous Marketing Technology Landscape graphic lists 8000 tech tools for marketers, up from 3800 in 2016. How many of them do you need? How many will drive business outcomes?
To help reduce the stress related to martech planning, I’m offering a simple model formed of layers. Each layer alone solves a crucial marketing use case for a B2C brand, and in a modern martech stack needs to pass data to the other layers. Netcore regularly uses this model to help our customers in planning martech purchases.
Your stack contains a Data Layer, Engagement Layer, Experience Layer, Content Layer, and Communications Layer.
Your data layer is where your data lives and generates insights. This layer should provide you with a single source of truth so that you don’t face the frustration of pulling out reports from each tool. It should also provide you with a unified view of your customers across all your touchpoints and activities.
Depending on your company’s level of data maturity, you have three options: build your own data warehouse and models, use a CDP, or do both. Behind the scenes, most CDPs are built the same way that your own data team would build a data layer – a Snowflake or BigQuery data warehouse, data ingestion tools, resolution models, and visualization tools. If you have the ability to build this in-house, you can end up with a solution that is custom-designed for your industry, customers and techstack. Obviously, this is a lot of work (and has high dependability on internal teams), which is why off-the-shelf CDPs exist for marketers. You get most of these elements prebuilt and ready to use. The limitation is that your data is structured in the CDP for a single purpose – you can’t do other things with it - and most CDPs need to accommodate a wide range of industries and customer types, and forms of input data.
The third option is to use both. Create your own data warehouse to structure the data, and then use the CDP for identity resolution and easy marketing reporting.
The engagement layer is where you plan omnichannel campaigns to customer segments. These campaigns can be short-term initiatives like an offer, or a longer-term approach to improving your onboarding, increasing loyalty or reducing cart abandonment. The tools here will let you create precise customer segments and plan multi-step messaging flows that cover a range of communication channels.
These are the tools that many marketing teams will already have the most familiarity with and form a core part of daily activity. The evolution is in how these tools pass data between layers.
The experience layer helps you define and optimize your customer's experience while they interact with your digital assets – usually website and app, but also support and service systems.
From Netcore’s perspective, there are three important elements here for B2C brands.
Product Recommendation: Creating a shopping experience for a small number of products is easy, but as you add more products, the complexity grows. You end up with multilevel category structures to organize the products into logical groups and an ever-growing number of tags to help with discovery. A Product Recommendation system is an AI model that predicts the products that a customer is most likely to engage with. This reduces the need for a customer to correctly understand and interact with the structure/search process that you have developed. Ecommerce brands can see a significant uplift in sales or engagement by implementing one of these models.
Content Recommendation – change the content you show a customer based on what you know about them. For example, geographical personalization could show different graphics, language, or offers based on the user's location. You can also present content based on past experience. If a user researches car insurance on your website, when they return, your homepage banner can be for a car insurance product
Think of content as having two components: the front and back end. The front end is what your customers see; the back end is where you store and manage the content. Traditionally each digital asset required both. Your website has a web CMS where you log in to update the content, and your app has a different CMS to update app content.
Modern CMS are called ‘headless’ or ‘decoupled’. They specialize in managing all content in one place. The content is then delivered via API to any of your assets – a website, e-commerce store, apps, service documentation, digital display screens, POS systems, kiosks etc.
As the number of devices and communication channels expands, brands face real challenges in effectively communicating with customers. Not only are there more channels than ever – email, SMS, voice, app and web notifications, WhatsApp and other messaging tools – but each one has a different format and process for delivery and monitoring. Suppose your emails are going in spam, or your app notifications are not delivered. In that case, your efforts to create the communication are wasted, and your engagement data is inaccurate, not to mention the opportunity cost of failing to reach the customer.
To manage communication delivery, brands should look to a CPaaS (communications platform as a service) partner who can manage each ‘pipe’. For email, the CPaaS partner should be able to ensure high inbox delivery, for app notifications, they should have different systems for sending the notification depending on the phone model, so if one fails, there is a backup option.
Marketers need to face the reality that our work will only become more data-driven and more tech-dependent. Various marketing budget surveys have found that martech is now 20-25% of marketing spends. Next year there will probably be new data tools, new messaging channels, and new regulations around data and privacy. The same the year after that.
You can make these changes easier by clearly understanding your tech stack and the layers that form it. For example, a new messaging channel should be connected by your CPaaS partner in the communications layer to the engagement layer, which should pass the final data to the data layer.
Review your existing tech stack to see how the solutions form each layer, and how they connect with other layers. This model will help you to identify gaps in your current stack and evaluate new tools.